| PointsUpdatemp {adlift} | R Documentation |
PointsUpdatemp
Description
This function performs the update lifting step using a given configuration of neighbours and boundary handling.
Usage
PointsUpdatemp(X, coeff, nbrs, newnbrs, index, remove, pointsin,
weights, lengths)
Arguments
X |
the vector of grid values. |
coeff |
the vector of detail and scaling coefficients at that step of the transform. |
nbrs |
the indices (into X) of the neighbours to be used in the lifting step. |
newnbrs |
as nbrs, but repeated according to the multiple point structure of the grid. |
index |
the indices into pointsin of nbrs, the neighbours of remove. |
remove |
the index (into X) of the point to be removed. |
pointsin |
The indices of gridpoints still to be removed. |
weights |
the prediction weights obtained from the regression in the prediction step of the transform. |
lengths |
the vector of interval lengths at the present step of the transform (to be updated). |
Details
The procedure performs a minimum norm update lifting step. Firstly the interval lengths are updated using the coefficients obtained. Secondly, the scaling and detail coefficient list is modified using the new interval lengths.
Value
coeff |
vector of (modified) detail and scaling coefficients to be used in the next step of the transform. |
lengths |
the vector of interval lengths after the update step of the transform. |
r |
the index into pointsin of remove. |
N |
length(pointsin). |
weights |
The regression coefficients used in prediction. |
alpha |
the update weights used to update lengths and coeff. |
Author(s)
Matt Nunes (nunesrpackages@gmail.com), Marina Knight
See Also
AdaptNeighmp, AdaptPredmp, CubicPredmp, fwtnpmp, LinearPredmp,
QuadPredmp, UndoPointsUpdatemp
Examples
#read in data with multiple values...
data(motorcycledata)
times<-motorcycledata$time
accel<-motorcycledata$accel
short<-adjustx(times,accel,"mean")
X<-short$sepx
coeff<-short$sepx
g<-short$g
coefflist<-list()
for (i in 1:length(g)){
coefflist[[i]]<-accel[g[[i]]]
}
I<-intervals(X,"reflect")
lengths<-lengthintervals(X,I,neighbours=2,closest=TRUE)
#work out neighbours of point to be removed (31)
out<-getnbrs(X,31,order(X),2,TRUE)
nbrs<-out$n
nbrs
newnbrs<-NULL
for (i in 1:length(nbrs)){
newnbrs<-c(newnbrs,rep(nbrs[i],times=length(g[[nbrs[i]]])))
}
#work out repeated neighbours using g...
newnbrs
p<-AdaptNeighmp(order(X),X,coefflist,coeff,nbrs,newnbrs,31,TRUE,2,"ave",g)
nbrs<-p$newinfo[[3]]
nbrs
newnbrs<-NULL
for (i in 1:length(nbrs)){
newnbrs<-c(newnbrs,rep(nbrs[i],times=length(g[[nbrs[i]]])))
}
newnbrs
coefflist[[31]]<-p$results[[6]][31]
u<-PointsUpdatemp(X,coefflist,p$newinfo[[2]],newnbrs,p$newinfo[[3]],31,
order(X),p$results[[4]],lengths)
#
#and here is the updated coefficient list...
u$coeff